Shipping delay prediction device, shipping delay prediction method, and shipping delay prediction program

Abstract

To predict with high accuracy whether product shipments will meet deadlines. [Solution] The shipping delay prediction device includes an order processing means that inputs order data including the planned shipping date, delivery date, customer, product, quantity ordered, and order number, calculated using the shipping lead time obtained from the customer lead time master with the order date and delivery date-customer as keys, and based on the order data, for each product, it calculates the planned inventory quantity at the planned shipping date as current inventory - planned shipping quantity + planned incoming quantity, and calculates the planned shipping date using the manufacturing lead time obtained from the manufacturing lead time master with the current date + product as keys, and the planned inventory quantity

Description

Technical Field

[0001] The present invention relates to a shipping delay prediction device, a shipping delay prediction method, and a shipping delay prediction program.

Background Art

[0002] For example, delivery date management in the manufacturing industry is an important task because it greatly affects differentiation from competing companies and trust from customers (such as clients). If a delivery delay occurs, it causes a decrease in customer satisfaction and may even lead to contract cancellation in some cases. Conventionally, as a system for performing delivery date management, for example, there is Patent Document ①.

Prior Art Documents

Patent Documents

[0003]

Patent Document ①

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, conventionally, there has been a problem that it is impossible to accurately predict whether the shipment of a product will meet the customer delivery date.

[0005] The present invention has been made in view of the above, and an object thereof is to provide a shipping delay prediction device, a shipping delay prediction method, and a shipping delay prediction program capable of accurately predicting whether the shipment of a product will meet the delivery date.

Means for Solving the Problems

[0006] To solve the above-mentioned problems and achieve the objective, the present invention provides a shipping delay prediction device equipped with a control unit, wherein the control unit is configured to access a customer lead time master, which is registered as associating a customer with the shipping lead time, which is the number of days from shipment to delivery to the customer, and a manufacturing lead time master, which is registered as associating a product with the manufacturing lead time, which is the number of days from the start of manufacturing to the date when the product can be shipped, and includes order processing means for inputting order data including the planned shipping date, delivery date, customer, product, number of orders, and order number, calculated using the shipping lead time obtained from the customer lead time master with the order date and delivery date-customer as keys, and shipping delay prediction means for determining products where the planned inventory quantity at the time of the planned shipping date is calculated as current inventory - planned shipping quantity + planned incoming quantity based on the order data, and the planned date when the product can be shipped is calculated using the manufacturing lead time obtained from the manufacturing lead time master with the current date + product as keys, and determining products where the planned inventory quantity < number of orders and the planned shipping date < planned shipping date as urgent products for which shipping delays are predicted.

[0007] Furthermore, according to a preferred embodiment of the present invention, the shipping delay prediction means may further create and output a shipping delay prediction list for products where planned inventory < number of orders, including the order date, planned shipping date, planned shipping date, delivery date, customer, product, number of orders, planned inventory, the number of shortages calculated as |planned inventory - number of orders|, and an express item flag indicating whether or not it is an express item.

[0008] Furthermore, according to a preferred embodiment of the present invention, the control unit may further include production planning means for creating and outputting production planning data, which includes the product, the planned production quantity which is the shortage, the manufacturing start date which is the current date, and the manufacturing delivery date which is the scheduled shipping date, based on the shipment delay prediction list.

[0009] Furthermore, according to a preferred embodiment of the present invention, the production plan data may be configured to be modifiable by the operator.

[0010] Furthermore, in order to solve the above-mentioned problems and achieve the objectives, the present invention provides a method for predicting shipping delays, which is executed by an information processing device equipped with a control unit, wherein the control unit is configured to access a customer lead time master, which is registered in association with a customer and a shipping lead time, which is the number of days from shipment to delivery to the customer, and a manufacturing lead time master, which is registered in association with a product and a manufacturing lead time, which is the number of days from the start of manufacturing to the date when the product can be shipped, and the method is characterized by including an order input step, which is executed by the control unit, in which order data is entered, including the planned shipping date, delivery date, customer, product, number of orders, and order number, calculated using the order date, delivery date-customer as the key and the shipping lead time obtained from the customer lead time master, and the planned shipping date, which is calculated using the order date, delivery date-customer as the key and the customer, and a shipping delay prediction step, which is executed by the control unit, which is executed in order input step, which is entered in order data including the order date, the planned inventory quantity at the time of the planned shipping date, calculated as current inventory quantity - planned shipping quantity + planned incoming quantity, the planned shipping date, calculated using the manufacturing lead time obtained from the manufacturing lead time master, which is calculated using the current date + product as the key and determines products where planned inventory quantity < number of orders and planned shipping date < planned shipping date as urgent products for which shipping delays are predicted.

[0011] Furthermore, in order to solve the above-mentioned problems and achieve the objective, the present invention provides a shipping delay prediction program to be executed by an information processing device equipped with a control unit, wherein the control unit is configured to access a customer lead time master, which is registered as associating a customer with the shipping lead time, which is the number of days from shipment to delivery to the customer, and a manufacturing lead time master, which is registered as associating a product with the manufacturing lead time, which is the number of days from the start of manufacturing to the time when it can be shipped, and the control unit receives the shipping lead time obtained from the customer lead time master using the order date and delivery date-customer as keys. The program is characterized by a shipping delay prediction process that executes the following steps: an order entry process in which order data including the scheduled shipping date, delivery date, customer, product, number of orders, and order number calculated by the system is entered; and a shipping delay prediction process in which, based on the order data, the planned inventory quantity at the scheduled shipping date for each product is calculated as current inventory - scheduled shipping quantity + scheduled incoming quantity, the scheduled shipping date is calculated using the current date + product as the key and the manufacturing lead time obtained from the manufacturing lead time master, and products where the planned inventory quantity < number of orders and the scheduled shipping date < scheduled shipping date are determined to be urgent items for which shipping delays are expected. [Effects of the Invention]

[0012] The present invention has the effect of making it possible to predict with high accuracy whether product shipments will be made on time. [Brief explanation of the drawing]

[0013] [Figure 1] Figure 1 is a block diagram showing an example of the configuration of the shipping delay prediction device according to this embodiment. [Figure 2] Figure 2 shows an example of the configuration of a customer lead time master. [Figure 3] Figure 3 shows an example of the configuration of a manufacturing lead time master. [Figure 4] Figure 4 is a diagram illustrating the overall processing flow of the control unit of the shipment delay prediction device in this embodiment. [Figure 5]FIG. 5 is a diagram for explaining a specific example of the processing of the control unit of the shipping delay prediction device in the present embodiment. [Figure 6] FIG. 6 is a diagram for explaining a specific example of the processing of the control unit of the shipping delay prediction device in the present embodiment. [Figure 7] FIG. 7 is a diagram for explaining a specific example of the processing of the control unit of the shipping delay prediction device in the present embodiment. [Figure 8] FIG. 8 is a diagram for explaining a specific example of the processing of the control unit of the shipping delay prediction device in the present embodiment. [Figure 9] FIG. 9 is a diagram for explaining a specific example of the processing of the control unit of the shipping delay prediction device in the present embodiment. [Figure 10] FIG. 10 is a diagram for explaining a specific example of the processing of the control unit of the shipping delay prediction device in the present embodiment. [Embodiments of the Invention]

[0014] Hereinafter, embodiments of a shipping delay prediction device, a shipping delay prediction method, and a shipping delay prediction program according to the present invention will be described in detail based on the drawings. Note that the present invention is not limited to the present embodiment.

[0015] [1. Overview] The overview of the present invention will be described in the order of [1-1. Background and Problems], [1-2. Solution], and [1-3. Effects]. <00​​​​​​​​​​​​By efficiently and accurately performing the above operations, it is possible to prevent delivery delays.

[0018] [1-2. Solution] In the present invention, in order to prevent delivery delays of products, it is predicted with high accuracy whether the shipment of products can meet the customer's delivery date. Specifically, at the time of receiving an order for a product, referring to the production lead time master and the customer lead time master from the current date with respect to the planned inventory and the customer delivery date, if the planned inventory at the time of shipment < the number of orders received, and the planned shipment date (= customer delivery date - shipment lead time) < the planned available shipment date (= current date + production lead time), it is determined as an urgent product for which a shipment delay is predicted, thereby predicting the shipment delay with high accuracy. Also, by creating a shipment delay prediction list, it becomes possible to identify in advance products that cannot meet the customer delivery date and take countermeasures. Furthermore, by creating production plan data for urgent products, the production planning work for urgent products can be made more efficient.

[0019] [1-3. Effects] The present invention has the following effects. (1) It is possible to accurately determine products for which delivery delays are expected. (2) It is possible to prevent delivery delays. Early adjustment of the production plan is possible, and by making adjustments to production early, the manufacturing work of products can be made more efficient, and it is possible to prevent delays in the customer delivery date. (3) It is possible to improve customer satisfaction. Events that lead to a decline in service quality such as delivery delays can be reduced, and customer satisfaction can be improved.

[0020] The shipment delay prediction device of the present invention can be widely used in manufacturing industries and the like. [2. Configuration] The configuration of the shipment delay prediction device 100 according to the present embodiment will be described with reference to FIG. 1 and the like. FIG. 2 is a block diagram showing an example of the configuration of the shipment delay prediction device 100 of the present embodiment.

[0021] The shipping delay prediction device 100 is a commercially available desktop personal computer. However, the shipping delay prediction device 100 is not limited to stationary information processing devices such as desktop personal computers, but may also be portable information processing devices such as commercially available notebook personal computers, PDAs (Personal Digital Assistants), smartphones, and tablet personal computers.

[0022] As shown in Figure 1, the shipping delay prediction device 100 comprises a control unit 102, a communication interface unit 104, a storage unit 106, and an input / output interface unit 108. Each component of the shipping delay prediction device 100 is connected to communicate via any communication path.

[0023] The communication interface unit 104 connects the shipping delay prediction device 100 to the network 300 via communication devices such as routers and wired or wireless communication lines such as dedicated lines. The communication interface unit 104 has the function of communicating data with other devices via communication lines. Here, the network 300 has the function of connecting the shipping delay prediction device 100 with the server 200 and customer systems (sources) 400, etc., so that they can communicate with each other, and is, for example, the internet or a LAN (Local Area Network). Note that the data stored in the storage unit 106, which will be described later, may be stored in the server 200.

[0024] The input / output interface unit 108 is connected to an input device 112 and an output device 114. The output device 114 can be a monitor (including a home television), a speaker, or a printer. The input device 112 can be a keyboard, mouse, microphone, or a monitor that works in conjunction with the mouse to provide pointing device functionality. In the following, the output device 114 may be referred to as the monitor 114, and the input device 112 as the keyboard 112 or mouse 112. "Output" includes displaying on the monitor of the output device 114 and printing with the printer of the output device 114. Furthermore, user operations on information displayed on the monitor 114 using the input device 112, etc., may be referred to as "user operation via UI".

[0025] The memory unit 106 stores various databases, tables, and files. The memory unit 106 also stores computer programs that work in cooperation with the OS (Operating System) to give instructions to the CPU (Central Processing Unit) to perform various processes. As the memory unit 106, for example, memory devices such as RAM (Random Access Memory) and ROM (Read Only Memory), fixed disk devices such as hard disks, flexible disks, and optical disks can be used.

[0026] Furthermore, the storage unit 106 stores customer lead time master 106a, manufacturing lead time master 106b, current inventory data, shipping schedule data, receiving schedule data, shipping delay forecast list, production plan data, etc. Figure 2 shows an example of the configuration of customer lead time master 106a. Figure 3 shows an example of the configuration of manufacturing lead time master 106b.

[0027] As shown in Figure 2, the customer lead time master 106a can be composed of tables that associate and register customers (customer code and / or customer name) with shipping lead time. "Shipping lead time" is the number of days from shipment to delivery to the customer, and the further the distance, the longer the number of days.

[0028] As shown in Figure 3, the manufacturing lead time can be structured using a table that associates the product (product code and / or product name) with the manufacturing lead time (in days). "Manufacturing lead time" is the number of days from the start of manufacturing within the company until the product is ready for shipment.

[0029] Order data may include the order date, scheduled shipping date, delivery date, customer (customer code and / or customer name), product (product code and / or product name), order quantity, unit price, sales amount, and customer order number.

[0030] Current inventory data may include the product (product code and / or product name) and the current inventory quantity.

[0031] Shipping schedule data may include the shipping date, product (product code and / or product name), and shipping quantity (number of orders).

[0032] The incoming shipment data may include the expected arrival date, product (product code and / or product name), and expected quantity (order quantity).

[0033] The shipping delay forecast list may include the order date, scheduled shipping date, estimated shipping date, delivery date, customer (customer code and / or customer name), product (product code and / or product name), quantity ordered, planned inventory quantity, shortage quantity (=|planned inventory quantity - quantity ordered|), and an express item flag (express item = 1, non-express item = 0).

[0034] Production plan data may include product code, planned production quantity, manufacturing start date, and manufacturing lead date. "Planned production quantity" is the shortage quantity. "Manufacturing start date" is the current date. "Manufacturing lead date" is the planned date for shipment.

[0035] The control unit 102 is a CPU or similar component that comprehensively controls the shipment delay prediction device 100. The control unit 102 has internal memory for storing control programs such as the OS, programs that define various processing procedures, and required data, and executes various information processing based on these stored programs.

[0036] The control unit 102 is configured to access customer lead time master 106a, manufacturing lead time master 106b, current inventory data, shipping schedule data, receiving schedule data, shipping delay forecast list, production plan data, etc., which are stored in the storage unit 106. Customer lead time master 106a, manufacturing lead time master 106b, current inventory data, shipping schedule data, receiving schedule data, shipping delay forecast list, production plan data, etc. may be stored in another location (for example, server 200), as long as the control unit 102 can access them.

[0037] Functionally, the control unit 102 comprises an order processing unit 102a, a shipping delay prediction unit 102b, a production plan creation unit 102c, a master maintenance unit 102d, and a screen display control unit 102e. The control unit 102 manages current inventory data, shipping schedule data, and incoming shipment schedule data, and updates this data.

[0038] The order processing unit 102a imports an order file (e.g., CSV) from a source (e.g., a customer's system 400) via an EDI site or email, and based on the imported file, inputs order data including the order date, delivery date calculated using the delivery lead time obtained from the customer lead time master 106a with the delivery date-customer as the key, delivery date, customer, product, quantity, and customer order number, and stores it in the storage unit 106.

[0039] The shipping delay prediction unit 102b, for each product in the order data, refers to the current inventory data, the scheduled shipping data, and the scheduled incoming data to calculate the planned inventory quantity at the scheduled shipping date as current inventory quantity - scheduled shipping quantity + scheduled incoming quantity. It also calculates the scheduled shipping date using the manufacturing lead time obtained from the manufacturing lead time master 106b with the current date + product as the key. Products where the planned inventory quantity < number of orders and the scheduled shipping date < scheduled shipping date are determined to be urgent products for which shipping delays are predicted.

[0040] Furthermore, the shipping delay prediction unit 102b may also create a shipping delay prediction list for products where the planned inventory quantity is less than the number of orders, including the order date, planned shipping date, planned shipping date, delivery date, customer, product, number of orders, planned inventory quantity, the shortage quantity calculated as |planned inventory quantity - number of orders|, and an express item flag indicating whether or not it is an express item, store it in the storage unit 106, and display it on the shipping delay prediction list screen.

[0041] The production planning unit 102c creates production planning data based on the shipment delay forecast list, including the product, the planned production quantity (the shortage), the manufacturing start date (the current date), and the manufacturing delivery date (the scheduled shipping date). This data is stored in the storage unit 106 and also displayed on the production planning screen. The operator is configured to be able to modify the production planning data.

[0042] The master maintenance unit 102d performs editing such as inputting, adding, changing, and updating data in the customer lead time master 106a and the manufacturing lead time master 106b, for example, in response to the operator's operations on the master maintenance screen (not shown) displayed on the monitor 114.

[0043] The screen display control unit 102e controls the display of various screens (for example, the master maintenance screen, the shipping delay prediction list screen, the production plan screen, etc.) displayed on the monitor 114, and the acceptance of inputs on the screen.

[0044] [3. Specific examples] A specific example of the processing of the control unit 102 of the shipment delay prediction device 100 according to this embodiment will be described with reference to Figures 1 to 10.

[0045] [3-1. Overall Processing] Figure 4 is a flowchart illustrating the overall processing flow of the control unit 102 of the shipping delay prediction device 100. The overall processing flow of the control unit 102 of the shipping delay prediction device 100 will be explained with reference to Figure 4.

[0046] In Figure 4, the order processing unit 102a executes order data acceptance processing (step S1). Specifically, in order data acceptance processing, the order processing unit 102a imports an order file (e.g., CSV) from a source (e.g., the customer's system 400) via an EDI site or email, and based on the imported file, inputs order data including the order date, the scheduled shipping date calculated using the shipping lead time obtained from the customer lead time master 106a with the delivery date-customer as the key, the delivery date, the customer, the product, the quantity, and the customer order number, and stores it in the storage unit 106.

[0047] The shipping delay prediction unit 102b executes the shipping delay prediction list output process (step S2). Specifically, in the shipping delay prediction list output process, the shipping delay prediction unit 102b refers to the current inventory data, shipping schedule data, and incoming schedule data for each product in the order data, calculates the planned inventory quantity at the scheduled shipping date as current inventory quantity - scheduled shipping quantity + incoming quantity, and calculates the scheduled shipping date using the manufacturing lead time obtained from the manufacturing lead time master 106b with the current date + product as the key. Products where planned inventory quantity < number of orders and scheduled shipping date < scheduled shipping date are determined to be urgent items for which shipping delays are predicted. For products where planned inventory quantity < number of orders, a shipping delay prediction list is created that includes the order date, scheduled shipping date, scheduled shipping date, delivery date, customer, product, number of orders, planned inventory quantity, the shortage quantity calculated as |planned inventory quantity - number of orders|, and an urgent item flag indicating whether or not it is an urgent item, and stores it in the storage unit 106, as well as displaying it on the shipping delay prediction list screen.

[0048] The production plan creation unit 102c executes the production plan data output process (step S3). Specifically, in the production plan data output process, the production plan creation unit 102c creates production plan data based on the shipment delay forecast list, including the product, the planned production quantity which is the shortage, the manufacturing start date which is the current date, and the manufacturing delivery date which is the scheduled shipping date. This data is stored in the storage unit 106 and also displayed on the production plan screen. The operator is configured to be able to modify the production plan data.

[0049] [3-2. Sample Data] Referring to Figures 5 to 10, a specific example of the processing of the control unit 102 of the shipping delay prediction device 100 will be explained. Figures 5 to 10 are diagrams showing sample data to illustrate a specific example of the processing of the control unit 102 of the shipping delay prediction device 100.

[0050] (S1: Order data acceptance processing) The order data acceptance process will be explained in detail with reference to Figures 5 and 6. The order processing unit 102a imports an order file (e.g., CSV) from the customer's system 400 via an EDI site or email, and based on the imported file (the imported order file is referred to as the "import file"), it inputs order data including the order date, scheduled shipping date calculated using the shipping lead time obtained from the customer lead time master 106a with the order date and delivery date-customer as keys, delivery date, customer, product, quantity, and customer order number, and stores it in the storage unit 106.

[0051] Figure 5 shows an example of data in an import file. The import file contains the following fields: order date, scheduled shipping date, delivery date, customer code, customer name, product code, product name, quantity, unit price, sales amount, and customer order number. In the example shown in the figure, the first row contains: order date "2024 / 11 / 14", scheduled shipping date "blank", delivery date "2024 / 12 / 13", customer code "T0001", customer name "○○ Corporation", product code "31008", product name "wire spring 1", quantity "10", unit price "100", sales amount "1,000", and customer order number "C00001". The scheduled import shipping date is "blank", so the scheduled import shipping date is calculated and set using the following method, entered as order data, and stored in the storage unit 106.

[0052] For the imported file, the system uses the customer as the key, references the customer lead time master 106a to obtain the shipping lead time, calculates and sets the scheduled shipping date, and stores it in the storage unit 106 as order data. The scheduled shipping date is calculated as customer delivery date - shipping lead time.

[0053] Figure 6(A) shows an example of the configuration of the customer lead time master 106a. The customer lead time master 106a can be composed of tables that associate customer codes, customer names, and shipping lead times. "Shipping lead time" is the number of days from shipment until delivery to the customer, and the number of days increases with distance. In the example shown in the figure, the first row is customer code "T0001", customer name "○○ Corporation", and shipping lead time "3", the second row is customer code "T0002", customer name "△△ Corporation", and shipping lead time "4", and the third row is customer code "T0002", customer name "□□ Corporation", and shipping lead time "1".

[0054] Figure 6(B) shows an example of order data. The order data includes the following fields: order date, scheduled shipping date, delivery date, customer code, customer name, product code, product name, quantity, unit price, sales amount, and customer order number. For the customer code "T0001" in the first row, the scheduled shipping date is calculated as delivery date "2024 / 12 / 13" - shipping lead time "3" = "2024 / 12 / 10". For the customer code "T0002" in the second row, the scheduled shipping date is calculated as delivery date "2024 / 12 / 20" - shipping lead time "4" = "2024 / 12 / 16". For the customer code "T0003" in the third row, the scheduled shipping date is calculated as delivery date "2024 / 12 / 3" - shipping lead time "1" = "2024 / 12 / 1".

[0055] (S2: Processing to output the shipping delay prediction list) The process for outputting the shipping delay prediction list will be explained in detail with reference to Figures 7 to 9. The shipping delay prediction unit 102b, for each product in the order data, refers to the current inventory data, the scheduled shipping data, and the scheduled incoming data to calculate the planned inventory quantity at the scheduled shipping date as current inventory quantity - scheduled shipping quantity + scheduled incoming quantity, and calculates the scheduled shipping date using the manufacturing lead time obtained from the manufacturing lead time master 106b with the current date + product as the key. Products where planned inventory quantity < number of orders and scheduled shipping date < scheduled shipping date are determined to be urgent products for which shipping delays are predicted. Furthermore, for products where planned inventory quantity < number of orders, the unit creates and outputs a shipping delay prediction list that includes the order date, scheduled shipping date, scheduled shipping date, delivery date, customer, product, number of orders, planned inventory quantity, the shortage quantity calculated as |planned inventory quantity - number of orders|, and an urgent product flag indicating whether or not it is an urgent product.

[0056] For each product in the order data, the planned inventory quantity is calculated using the following formula based on the planned shipping data and planned incoming data up to the scheduled shipping date: Planned inventory quantity = Current inventory quantity - Planned shipping quantity + Planned incoming quantity

[0057] Figure 7(A) shows an example of current inventory data. The current inventory data includes the fields for product code, product name, and current inventory quantity. In the example shown in the figure, the first row contains product code "31008", product name "Wire Spring 1", and current inventory quantity "15".

[0058] Figure 7(B) shows an example of shipment schedule data. The shipment schedule data includes the following items: shipment date, part number code, product name, and shipment quantity (order quantity). In the example shown in the figure, the first row contains the shipment date "2024 / 12 / 2", product code "31008", product name "wire spring 1", and shipment quantity (order quantity) "4".

[0059] Figure 7(C) shows that incoming shipment data may include the incoming shipment date, product code, product name, and incoming shipment quantity (order quantity). In the example shown in the figure, the first row contains the incoming shipment date "2024 / 12 / 2", product code "352196", product name "Disc spring 1", and incoming shipment quantity (order quantity) "7".

[0060] As shown in Figure 7(D), the planned inventory quantity at the scheduled shipping date of the order data is calculated. The planned inventory quantity is calculated as follows: Planned inventory quantity = Current inventory quantity - Scheduled shipping quantity + Scheduled incoming quantity. Orders where the planned inventory quantity at the scheduled shipping date < Order quantity are included in the output of the shipping delay prediction list and production plan data.

[0061] The first row contains the scheduled shipping date "2024 / 12 / 10", product code "31008", product name "Wire Spring 1", and planned inventory quantity "2 (=15-4-9)". Since the planned inventory quantity "2" < the number of orders "10", this row will be included in the output of the shipping delay prediction list and production plan data.

[0062] The second row shows the planned shipping date "2024 / 12 / 16", product code "352057", product name "Leaf Spring 2", and planned inventory quantity "3". Since the planned inventory quantity "3" < the number of orders "5", this row will be included in the output of the shipping delay prediction list and production plan data.

[0063] The third line shows a planned shipping date of "2024 / 12 / 1", product code "352196", product name "Disc spring 1", and planned inventory quantity of "8". Since the planned inventory quantity of "8" > the number of orders "5", this line will be excluded from the output of the shipping delay prediction list and production plan data.

[0064] The estimated shipping date is calculated using the manufacturing lead time obtained from the manufacturing lead time master 106b, with the key being "Estimated Shipping Date = Current Date + Product Code". The current date is automatically set in the system. Here, the current date is set to "2024 / 11 / 15".

[0065] Figure 8(A) shows an example of the configuration of the manufacturing lead time master 106b. The manufacturing lead time master 106b can be composed of tables that associate product codes and manufacturing lead times (days). "Manufacturing lead time" is the number of days from the start of manufacturing within the company until the product can be shipped. In the example shown in the figure, the first row is product code "31008" and manufacturing lead time "20", the second row is product code "352057" and manufacturing lead time "35", and the third row is product code "3352196" and manufacturing lead time "10".

[0066] In this example, the estimated shipping dates for order data are as follows: for product code "31008", it is 2024 / 11 / 15 + 20 = 2024 / 12 / 5; for product code "352057", it is 2024 / 11 / 15 + 35 = 2024 / 12 / 20; and for product code "352196", it is 2024 / 11 / 15 + 10 = 2024 / 11 / 25.

[0067] Products where the planned inventory quantity is less than the number of orders, and the planned shipping date is less than the expected shipping date, are classified as express items where shipping delays are expected.

[0068] In Figure 8(B), comparing the scheduled shipping date and the expected shipping date, for product code "31008", the scheduled shipping date "2024 / 12 / 10" > expected shipping date "2024 / 12 / 5", so it is not subject to express shipping (express shipping flag = 0). For product code "352057", the scheduled shipping date "2024 / 12 / 16" < expected shipping date "2024 / 12 / 20", so it is subject to express shipping (express shipping flag = 1).

[0069] For products where the planned inventory quantity is less than the number of orders, a shipping delay forecast list is created and stored in the memory unit 106, and also displayed on the shipping delay forecast list screen. Figure 8(C) shows an example of the data in the shipping delay forecast list. The shipping delay forecast list includes the following items: order date, planned shipping date, planned shipping date, delivery date, customer code, customer name, product code, number of orders, planned inventory quantity, shortage quantity (=|planned inventory quantity - number of orders|), and urgent item flag (urgent item=1, non-urgent item=0). In the example shown in the figure, the urgent item flag is 0 for product code "31008", and the urgent item flag is 1 for product code "352057". If the urgent item flag is 1, internal manufacturing adjustments and delivery date adjustments with the customer will be necessary.

[0070] Figure 9 shows an example of the display screen for the shipment delay forecast list. The reference date is initially set to the current date. The items subject to shipment delays can be viewed on the screen. The "F9: Output" button allows you to output the target data in the format for importing production plan data.

[0071] (S3: Production plan data output processing) Referring to Figure 10, the production plan data output process will be explained in detail. Based on the shipment delay forecast list, the production plan creation unit 102c creates production plan data including the product, the planned production quantity which is the shortage, the manufacturing start date which is the current date, and the manufacturing delivery date which is the scheduled shipping date, and stores it in the storage unit 106 and also displays it on the production plan screen. On the production plan screen, for example, the person in charge of production management (operator) can modify (edit) the production plan data. For example, if it is possible to adjust the manufacturing delivery date, the manufacturing delivery date can be modified to ensure that the shipment is made on time.

[0072] Figure 10 shows an example of production plan data. The production plan data includes the following fields: product code, planned production quantity, manufacturing start date, and manufacturing lead date. "Planned production quantity" is the shortage quantity. "Manufacturing start date" is the current date. "Manufacturing lead date" is the planned date for shipment.

[0073] As described above, according to this embodiment, for example, an order processing unit 102a imports an order file (e.g., CSV) from a source (e.g., customer's system 400) via an EDI site or email, and based on the imported file, inputs order data including the order date, delivery date, customer, product, quantity, and customer order number, calculated using the delivery lead time obtained from the customer lead time master 106a with the order date and delivery date-customer as keys, and stores it in the storage unit 106. The shipping delay prediction unit 102b, for each product in the order data, refers to the current inventory data, delivery date data, and incoming delivery date data to calculate the planned inventory quantity at the time of the delivery date as current inventory quantity - delivery date quantity + incoming delivery quantity, and calculates the planned shipping date using the manufacturing lead time obtained from the manufacturing lead time master 106b with the current date + product as keys, and determines products where the planned inventory quantity < order quantity and delivery date < planned shipping date as urgent products for which a shipping delay is expected. As such, it is possible to predict with high accuracy whether product shipments will be made on time.

[0074] [4. Contribution to the United Nations-led Sustainable Development Goals (SDGs)] This embodiment can contribute to improving operational efficiency and promoting appropriate management decisions by companies, thereby contributing to SDGs Goals 8 and 9.

[0075] Furthermore, this embodiment can contribute to reducing waste and promoting paperless and digital processes, thereby contributing to SDGs Goals 12, 13, and 15.

[0076] Furthermore, this embodiment can contribute to strengthening control and governance, thereby enabling contributions to SDG Goal 16.

[0077] [5. Other Embodiments] In addition to the embodiments described above, the present invention may be implemented in various different embodiments within the scope of the technical idea described in the claims.

[0078] For example, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods.

[0079] Furthermore, the processing procedures, control procedures, specific names, information including parameters such as registration data and search conditions for each process, screen examples, and database configuration shown in this specification and in the drawings may be changed at will unless otherwise specified.

[0080] Furthermore, with respect to the shipment delay prediction device 100, each component shown in the illustration is a functional concept and does not necessarily need to be physically configured as shown.

[0081] For example, the processing functions of the shipping delay prediction device 100, particularly those performed by the control unit 102, may be implemented in whole or in part by a CPU and a program interpreted and executed by the CPU, or they may be implemented as wired logic hardware. The program is recorded on a non-temporary computer-readable recording medium containing programmed instructions for the information processing device to execute the processing described in this embodiment, and is mechanically read by the shipping delay prediction device 100 as needed. That is, a storage unit such as ROM or HDD (Hard Disk Drive) records a computer program that works in cooperation with the OS to give instructions to the CPU and perform various processing. This computer program is executed by being loaded into RAM and works in cooperation with the CPU to constitute the control unit.

[0082] Furthermore, this computer program may be stored on an application program server connected to the shipping delay prediction device 100 via any network, and it is possible to download all or part of it as needed.

[0083] Furthermore, the program for executing the processing described in this embodiment may be stored on a non-temporary computer-readable recording medium, or it may be configured as a program product. Here, "recording medium" includes any "portable physical medium" such as memory cards, USB (Universal Serial Bus) memory, SD (Secure Digital) cards, flexible disks, magneto-optical disks, ROMs, EPROMs (Erasable Programmable Read Only Memory), EEPROMs (Registered Trademark) (Electrically Erasable and Programmable Read Only Memory), CD-ROMs (Compact Disk Read Only Memory), MOs (Magneto-Optical disks), DVDs (Digital Versatile Disks), and Blu-ray (Registered Trademark) Discs.

[0084] Furthermore, "program" refers to a data processing method described in any language or writing method, regardless of its format, such as source code or binary code. Note that "program" is not necessarily limited to a single, monolithic structure; it also includes distributed structures composed of multiple modules or libraries, and those that work in cooperation with other programs, such as an operating system, to achieve their functions. Regarding the specific configuration and reading procedures for reading the recording medium in each device shown in the embodiments, as well as the installation procedures after reading, well-known configurations and procedures can be used.

[0085] The various databases stored in the memory unit 106 include memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and optical disks, and store various programs, tables, databases, and web page files used for various processes and website provision.

[0086] Furthermore, the shipping delay prediction device 100 may be configured as an information processing device such as a known personal computer or workstation, or as an information processing device to which any peripheral devices are connected. Alternatively, the shipping delay prediction device 100 may be implemented by installing software (including programs or data, etc.) that enables the processing described in this embodiment onto the device.

[0087] Furthermore, the specific forms of distribution and integration of the devices are not limited to those shown in the figures, and all or part of them can be configured by functionally or physically distributing and integrating them in any unit according to various additions or functional loads. In other words, the embodiments described above may be implemented in any combination, or the embodiments may be implemented selectively. [Explanation of Symbols]

[0088] 100 Shipping Delay Prediction Device 102 Control Unit 102a Order Processing Unit 102b Shipping Delay Forecasting Section 102c Production Planning Department 102d Master Maintenance Department 102e Screen display control unit 104 Communication Interface Section 106 Storage section 106a Customer Lead Time Master 106b Manufacturing Lead Time Master 108 Input / Output Interface Section 112 Input device 114 Output device 200 servers 300 Networks 400 Customer Systems

Claims

1. A shipping delay prediction device equipped with a control unit, The control unit, The customer lead time master, which is registered by associating the customer with the shipping lead time, which is the number of days from shipment to delivery to the customer, A manufacturing lead time master, which is registered by associating the product with the manufacturing lead time, which is the number of days from the start of manufacturing to the day when the product can be shipped, It is configured to be accessible, An order processing means for inputting order data including the planned shipping date, delivery date, customer, product, order quantity, and order number, calculated using the order date, delivery date - customer as the key and the shipping lead time obtained from the customer lead time master, and Based on the aforementioned order data, the shipping delay prediction means calculates the planned inventory quantity at the scheduled shipping date for each product as current inventory - planned shipping quantity + planned incoming quantity, calculates the scheduled shipping date using the current date + product as the key and the manufacturing lead time obtained from the aforementioned manufacturing lead time master, and determines products where planned inventory quantity < number of orders and scheduled shipping date < scheduled shipping date as urgent products for which shipping delays are expected. A shipping delay prediction device characterized by being equipped with the following features.

2. The shipping delay prediction device according to claim 1 is further characterized in that the shipping delay prediction means creates and outputs a shipping delay prediction list for products where the planned inventory quantity < the number of orders, including the order date, planned shipping date, planned shipping date, delivery date, customer, product, number of orders, planned inventory quantity, the number of shortages calculated as |planned inventory quantity - number of orders|, and an express item flag indicating whether or not it is an express item.

3. The control unit further, The shipping delay prediction device according to claim 2, further comprising a production plan creation means for creating and outputting production plan data including the product, the planned production quantity which is the shortage, the manufacturing start date which is the current date, and the manufacturing delivery date which is the scheduled shipping date, based on the aforementioned shipping delay prediction list.

4. The shipment delay prediction device according to claim 3, characterized in that the production plan data is configured to be modifiable by the operator.

5. A method for predicting shipping delays, which is performed by an information processing device equipped with a control unit, The control unit, The customer lead time master, which is registered by associating the customer with the shipping lead time, which is the number of days from shipment to delivery to the customer, A manufacturing lead time master, which is registered by associating the product with the manufacturing lead time, which is the number of days from the start of manufacturing to the day when the product can be shipped, It is configured to be accessible, The control unit executes: An order entry process involves entering order data including the planned shipping date, delivery date, customer, product, order quantity, and order number, calculated using the order date, delivery date, and customer as keys and the shipping lead time obtained from the customer lead time master. Based on the aforementioned order data, the planned inventory quantity at the scheduled shipping date for each product is calculated as current inventory - planned shipping quantity + planned incoming quantity, and the scheduled shipping date is calculated using the current date + product as the key and the manufacturing lead time obtained from the aforementioned manufacturing lead time master. Products where planned inventory quantity < number of orders and scheduled shipping date < scheduled shipping date are determined to be urgent items for which shipping delays are expected. A method for predicting shipping delays, characterized by including the following:

6. A shipping delay prediction program to be executed by an information processing device equipped with a control unit, The control unit, The customer lead time master, which is registered by associating the customer with the shipping lead time, which is the number of days from shipment to delivery to the customer, A manufacturing lead time master, which is registered by associating the product with the manufacturing lead time, which is the number of days from the start of manufacturing to the day when the product can be shipped, It is configured to be accessible, The control unit, An order entry process involves entering order data including the planned shipping date, delivery date, customer, product, order quantity, and order number, calculated using the order date, delivery date, and customer as keys and the shipping lead time obtained from the customer lead time master. Based on the aforementioned order data, the planned inventory quantity at the scheduled shipping date for each product is calculated as current inventory - planned shipping quantity + planned incoming quantity, and the scheduled shipping date is calculated using the current date + product as the key and the manufacturing lead time obtained from the aforementioned manufacturing lead time master. Products where planned inventory quantity < number of orders and scheduled shipping date < scheduled shipping date are determined to be urgent items for which shipping delays are expected. A shipping delay prediction program to execute this.

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